PRo-Pat: Probabilistic Root-Pattern Bi-gram data language model for Arabic based morphological analysis and distribution.

ABSTRACT: Based on 29,192,662 html files obtained from the ClueWeb a bi-gram data language model for Arabic is constructed. The created dataset is considering standard types of bi-gram analysis, however with focus on the root-pattern paradigm in Arabic. Root-Pattern distributions in form of P(root|pattern), P(pattern|root) and P(pattern|pattern) are additionally estimated. The aspect of considering the Maximum Likelihood Estimation (MLE) on the root-pattern level as a higher-level of abstraction, has been widely neglected in Arabic research community despite its advantage in reducing ambiguities within Arabic morphological analysis and its impact on cognitive aspect on Arabic word perception [1]. In the preprocessing phase, the html files were converted to 974 unfiltered raw text files with the size

SUBMITTER: Haddad B 

PROVIDER: S-EPMC9852924 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature